Blurb::
Uses Latin Hypercube Sampling (LHS) to sample variables
Description::
The ``lhs`` keyword invokes Latin Hypercube Sampling as the means of
drawing samples of uncertain variables according to their probability
distributions.  This is a stratified, space-filling approach that
selects variable values from a set of equi-probable bins.

*Default Behavior*

Latin Hypercube Sampling is the default sampling mode in most contexts
(exception: multilevel_sampling).  To explicitly specify LHS in the
Dakota input file, the ``lhs`` keyword must appear in conjunction with
the ``sample_type`` keyword.

*Usage Tips*

Latin Hypercube Sampling is very robust and can be applied to any
problem.  It is fairly effective at estimating the mean of model
responses and linear correlations with a reasonably small number of
samples relative to the number of variables.
Topics::

Examples::

.. code-block::

    method
      sampling
        sample_type lhs
        samples = 20


Theory::

Faq::

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